1. Field of the Invention
The present invention relates to a resource management system capable of autonomously achieving two objects through learning resource management or control knowledge, the enhancement of system throughput and enhancement of the response of a system, and more particularly to a resource management system which, by a learning process acquires an allocation scheduling function of process units to resources attain the above two objects in a computer system.
2. Description of the Prior Art
As a representative case for a resource management system, the present status of the operating system (OS) for a large scale computer system is discussed.
The purpose of a resource management system which is one of the cores of the operating system for a large scale computer system is to utilize resources of the computer system as effectively as possible to enhance the performance (i.e. throughput) and improve the response as measured from the user. To this end, many resource management systems have been proposed. (For example, A. J. Bernstein & J. C. Sharp: A Policy Driven Scheduler for a Time-Sharing System, Comm. ACM, Vol. 14, No. 2, pp. 74-78 (1971); H. W. Lynch & J. B. Page: The OS/VS2 Release 2 System Resources Manager IBM System Journal, Vol. 13, No. 4, pp. 274-291 (1974).)
In those proposals, in order to achieve the above two objects, utilization factors of the resources and quantities of resource services provided to process units (program units which are called transactions in an on-line system, jobs in a batch processing system and commands in a TSS system) are periodically measured and resource allocation schedule controls are performed by schedulers in accordance with the degrees of deviation from preset target values or service functions.
In order to cause the system to perform resource allocation scheduling, it is necessary to preset various open parameters including parameters for specifying shapes of service functions.
FIG. 1 illustrates such situation. An aggregation 110 of process units 115 having various characteristics are inputted to a computer system 100. In order to achieve the above two objects under changing conditions, it is necessary for a manager (i.e. human operator) 130 using a computer system 100 to take in various monitor information 120 including the utilization status of the resources and optimize resource management policy parameters 150 such as the above-mentioned service function parameters, while referencing operating system manuals 140.
However, the characteristics of the process units to be processed are not stable (i.e. the quantities and the characteristics such as job mix vary with time) and it is uncertain whether and to what degree the above two objects are achieved by changing there adjustable parameters. Accordingly, it is very difficult to optimize these parameters. Even if it may be possible under stable environments, retry of parameter adjustments by a human operator is required each time the number of TSS terminals connected to the computer changes or real memory are enlarged, which are everyday affairs of widely used large scale computer systems.